Sentiment Analysis of Forest Fires on Social Media Networks Twitter Using the Long Short Term Memory (LSTM) Method
AZIZ ALFAUZI

Informasi Umum

Kode

23.04.6563

Klasifikasi

004 - Data processing, Computer science

Jenis

Karya Ilmiah - Skripsi (S1) - Reference

Subjek

Data Science, Social Media,

Dilihat

14 kali

Informasi Lainnya

Abstraksi

<p>Abstract-The topic of forest fires is of significant interest on social media platforms. In this case, Twitter has been used by 11.8<br /> million users as a means to spread information about forest fires. Twitter, a microblogging service launched on July 13, 2006, allows<br /> users to share information for free to themselves and others. Public sentiment related to forest fires can be analyzed through opinions<br /> and discussions on Twitter social media. This research aims to analyze the Sentiment of Forest Fires on Twitter Social Networks using<br /> the Long Short Term Memory (LSTM) Method. The research data was obtained by crawling the Twitter API using the keyword "forest<br /> fire." After crawling, 7,000 tweet texts were collected and labeled as "Negative" and "Positive." Through the preprocessing stage, using<br /> a 7,000 dataset, the TF-IDF accuracy of the developed LSTM model reached 68.14%. In addition, the GloVe expansion feature was<br /> performed with the Tweet corpus, which resulted in an increase in accuracy of 11.77% to 80.13% in the LSTM model. Meanwhile, the<br /> FastText expansion feature with the Common Crawl corpus also increased the accuracy by 11.99% to 80.59% on the LSTM model.</p>

• CII4E4 - TUGAS AKHIR

Koleksi & Sirkulasi

Tersedia 1 dari total 1 Koleksi

Pengarang

Penerbit

Sirkulasi

Download / Flippingbook